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The New Regionalism and Policy Interdependence
Leonardo Baccini Trinity College Dublin
Andreas Dür University College Dublin
[email protected] Abstract
Over the last twenty years, the number of bilateral and regional preferential trade agreements
in existence has increased very rapidly. Explanations of this development emphasize factors
such as the spread of democracy, deadlock in multilateral trade negotiations, and learning.
Our argument is that policy diffusion as a result of competition over market access is a
major driving force behind what has become known as the “new regionalism”. The causal
reasoning is that facing trade diversion, exporters excluded from a preferential trade
agreement are likely to mobilize and push their government into signing an agreement with
the country in which their exports are threatened. We test our argument against alternative
explanations in a quantitative analysis of the proliferation of preferential trade agreements
among 168 countries between 1990 and 2007. By showing that competition is indeed a major
cause of the new regionalism, the paper contributes to the literatures on regionalism and
policy diffusion.
Key words: preferential trade agreements, policy diffusion, interest groups, spatial interdependence, Cox model.
Current Version: October 2008 First Version: March 2008 Word Count: 12,297
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INTRODUCTION
A casual overview of major trade policy developments over the last two hundred years
suggests that preferential trade policies are contagious. The Cobden-Chevalier agreement
between France and the United Kingdom (1860) was the first of a large number of
preferential trade agreements that were concluded in the second half of the nineteenth
century.1 In the interwar years, major European powers moved in parallel to establish
sizeable preferential trading systems with their colonies. The 1960s saw the spread of
regional trade agreements that clearly were a response to the creation of the European
Economic Community (1958). Finally, since the early 1990s many countries in the world
have decided to adopt preferential trade policies, leading to the sharp increase in the number
of preferential agreements in existence that is known as the “new regionalism”.2
Several potential explanations exist for these developments. Different countries
concluding preferential trade agreements at the same time may be the result of a “domino
effect”.3 In this view, the negative externalities from the conclusion of an agreement make
excluded countries scramble for new agreements.4 Alternatively, learning and the spread of
ideas may make countries adopt similar trade policies at the same time. Still another
explanation for parallel trade policy choices can be found in the security externalities that
trade can have.5 If a trade agreement provides security benefits to participating countries, in
an anarchic world in which all countries strive for survival, excluded countries will be pushed
to conclude agreements as well. Moreover, if democracies find it beneficial to conclude
preferential trade agreements, a spread of democracy may create the impression of contagion
1 Lazer 1999; Pahre 2008. 2 Mansfield and Milner 1999. 3 Baldwin 1993. 4 See for example, Oye 1992; Mansfield 1998; Lazer 1999; Gruber 2000; Manger 2005; Dür 2007b. 5 Gowa 1994; Skålnes 1998.
2
among trade policies.6 Finally, developments in the international trading system may create
incentives for all or many countries to pursue similar trade policies.7 For instance, stagnation
of the process of multilateral trade liberalization may stimulate several countries at the same
time to pursue preferential trade policies. In short, a variety of explanations exist that at first
sight provide plausible accounts of the empirical observations outlined above.
In this paper, building on the “domino theory” proposed by Richard Baldwin8, we
argue that the proliferation of preferential trade agreements over the last two decades is an
indication of policy interdependence. Countries excluded from a preferential trade agreement
react by signing their own agreements, thus driving the phenomenon that we know as the
new regionalism. What we add to this explanation is a logic that makes explicit the political
processes at the domestic level that impel the domino effect. The puzzle is that before facing
commercial discrimination, excluded countries are satisfied with the status quo, but once they
feel the negative effects of a preferential trade agreement from which they are excluded, their
trade-policy orientation changes. What are the underlying domestic political processes that
drive this change in trade-policy orientation? Our response is that exporters lobby more
against losses of foreign market access than in favor of opportunities, hence causing a shift
in the balance of domestic interests once a country faces discrimination abroad.
We test this argument against alternative explanations in a quantitative analysis of the
proliferation of preferential trade agreements among 168 countries between 1990 and 2007.
In this empirical analysis, rather than only show that preferential trade agreements are
contagious, our aim is to show why they are so: because of competitive pressures, emulation,
or security externalities? In carrying out the analysis, we introduce several improvements
6 Mansfield et al. 2002. 7 Mansfield and Reinhardt 2003. 8 Baldwin 1993; 1997; 2006.
3
with respect to data and method to the quantitative literature on preferential trade
agreements. Most importantly, we invested substantial effort in establishing an authoritative
list of trade agreements. We also were very cautious in operationalizing our variables in order
to allow for an analysis that comes as close as possible to testing our causal mechanism. The
findings provide strong support for our argument. The choice by different countries to enter
preferential trade agreements is indeed interdependent; and the interdependence increases as
the negative externalities from existing agreements increase.
The paper hence is of relevance to the literature on regionalism in the world
economy. At the same time, we also make a contribution to a growing literature on policy
diffusion and policy interdependence.9 Increasingly, scholars of international political
economy realize that dyads are not independent of each other, and try to model the
interdependence among them.10 Policy interdependence, for example, has been shown to be
a driving force of the diffusion of bilateral investment treaties.11 We add to this literature by
taking seriously a recent call for accepting that “space is more than geography”12 when
establishing the spatial weights matrix that is used to examine policy diffusion. Moreover, we
introduce a new way of measuring the degree of dependence among two observations, which
includes attention to extra-dyadic relationships.
In the following, we first briefly outline the existing literature on the spread of
preferential trade agreements. This discussion shows that a large number of different
explanations for the new regionalism exist. We then establish our argument that focuses on
attempts at regaining market access as driving factor behind the sharp increase in the number
of preferential agreements over the last twenty years. After discussing our data and approach
9 See for example, Gleditsch and Ward 2000; Braun and Gilardi 2006; and Franzese and Hays 2008. 10 Neumayer and Plümper 2008. 11 Elkins et al. 2006. 12 Beck et al. 2006.
4
to testing the argument, we present our empirical findings. In the conclusion, we stress the
implications of our findings for studies on new regionalism and policy interdependence.
EXPLAINING THE NEW REGIONALISM
Over the last fifteen years, the number of dyads forming part of a preferential trade
agreement has increased sharply (see Figure 1). While in 1990, only about 250 pairs of
countries had a preferential trade agreement between them, the number stood at 1829 in
2007.13 With 14,028 dyads in our dataset in 200714, this means that no fewer than 13 percent
of all dyads have a preferential trade link among them. Obviously, the European Union,
owing to its large number of member countries and agreements concluded with third
countries, accounts for a sizeable number of these dyads. The signature of the EU accession
treaties with ten Central and Eastern European countries, for example, explains a large part
of the peak in agreements signed in 2003. This does not mean that the process is limited to
the EU, however. Our data show that across the world, the number of agreements being
signed is increasing. In particular, there is a growing number of South-South agreements and
of agreements involving Asian countries. Moreover, the EU’s increasing membership and
continued attractiveness as partner for preferential trade agreements is itself support for our
argument.
FIGURE 1 APPROXIMATELY HERE
What explains this proliferation of preferential trade agreements across the world? A
sizeable literature has been written that provides a series of different responses to this
13 Below we explain in some detail how we arrive at these numbers. 14 Since some countries, for example states in the area of the former Soviet Union, enter the dataset later than 1990, only 13,800 dyads are included for the whole period.
5
question. We distinguish five broad explanations, stressing the spread of ideas and
emulation, geopolitical balancing, common external shocks, common changes at the
domestic level, and competitive pressures. A first explanation for the new regionalism
stresses the spread of ideas and emulation. If specific trade policy ideas influence the trade
policies of different countries at the same time, such countries may all move in the same
direction, giving the impression of policy interdependence. Charles Kindleberger, for
example, contended that the period of free trade that Europe experienced in the nineteenth
century was a result of the spread of free trade ideas. In his words, “the countries of Europe
in this period should not be considered as independent economies whose reactions to
various phenomena can properly be compared, but rather as a single entity which moved to
free trade for ideological or perhaps better doctrinal reasons.”15
Alternatively, the perceived success of the trade policies of one or several countries
may lead to learning and emulation. Again, this would lead to the observation of parallel
trade policy choices. Suggesting such an influence, the economist Friedrich List, who in 1819
set up a pressure group to lobby for German economic unification, compared the situation
in Germany to that of France: “With envious eyes [traders from Germany] gaze across the
Rhine where a great nation can trade freely from the Rhine to the Pyrenees, from the Dutch
frontier to Italy without meeting with a single customs-house officer.”16 In the debate over
Great Britain’s unilateral adoption of free trade in the first half of the nineteenth century, the
argument that this would induce other countries to follow suit again had a prominent place.17
The principal idea was that other countries would perceive the benefits Great Britain accrued
from its free-trade policy and thus be convinced to follow the same course of action. Finally,
15 Kindleberger 1975, 51. 16 Cited in Birnie 1930, 72. 17 O’Brien 1976, 553.
6
the economic successes of the member countries of the European Economic Community
might have motivated economic integration in Latin America and Africa in the 1960s.18
Second, a spread of preferential trade agreements may result from the need for
balancing the trade-policy choices of other countries. Neorealist International Relations
theory argues that the anarchic structure of the international system makes states
apprehensive of increases in the power of other states, as these states may use their new
capabilities to attack them.19 Since preferential trade agreements that stimulate trade flows
may increase the wealth and hence the power of a country, excluded countries may be
concerned about such agreements.20 An agreement between two countries may thus force
other dyads to follow suit, to retain their current relative position vis-à-vis these countries.
According to this view, what we should witness is the development of rival trade blocs that
mirror security alliances.
Third, parallel trade policy choices can be a result of external shocks that affect all
countries in the system equally. The stagnation of the multilateral process of trade
liberalization, for example, may create incentives for states to pursue preferential trade
liberalization. Realizing that they cannot achieve better access to foreign markets by way of a
multilateral trade agreement, exporters in different countries may decide to lobby their
governments for the pursuit of preferential trade agreements. Alternatively, states may be
pushed to sign preferential trade agreements during multilateral trade talks, as such
agreements may increase their bargaining power at the level of the World Trade
Organization.21 The drawn out negotiations in the Uruguay Round and in the Doha
Development Agenda hence may explain the current proliferation of preferential trade
18 Pomfret 2001, 358. 19 Waltz 1979. 20 Gowa 1994. 21 Mansfield and Reinhardt 2003.
7
agreements. A final external shock that may explain the spread of preferential trade
agreements is the reduction of trade distance as a result of technological progress. Previous
research has shown that the distance between two countries and the remoteness of a dyad
from the rest of the world can explain whether a dyad forms part of the same trade
agreement.22 A decrease in trade distance hence may explain the boost in the number of
trade agreements that we observe over the last two decades.
Fourth, there may be changes at the domestic level that affect different countries at
the same time. Existing research has shown that democratic dyads are more likely to sign a
preferential trade agreement.23 The theoretical rationale given for this finding is that
democratic governments may use trade agreements as a signaling device vis-à-vis domestic
constituents. Following this view, the spread of democracy since the 1980s, which saw
countries in Latin America, Central and Eastern Europe, and Asia move towards democracy,
may thus explain the concurrent proliferation of preferential trade agreements.
Finally, competition for market access may explain the proliferation of trade
agreements. In this view, preferential trade agreements impose costs on excluded countries,
making the latter eager to join or to set up a rival agreement. Following this line of
reasoning, Kenneth Oye argued that discriminatory trade policies in the 1930s and the 1980s
had the unintended consequence of promoting further openness.24 Lloyd Gruber proposed
that the North American Free Trade Agreement (1994) was a consequence of Mexico’s
reaction to the creation of the Canada-United States free trade agreement (1988).25 Marc
Manger demonstrated that Japan concluded a trade agreement with Mexico because it feared
22 Baier and Bergstrand 2004. 23 Mansfield et al. 2002. 24 Oye 1992. 25 Gruber 2000.
8
exclusion from the North American Free Trade Agreement (NAFTA, 1994).26 Finally,
Andreas Dür showed how European discriminatory trade policies in the 1930s and the 1960s
led to an American reaction.27 In the following, we provide an argument that builds on these
studies.
THE PROTECTION-FOR-EXPORTERS ARGUMENT
The protection-for-exporters argument that we set out to explain the spread of trade
agreements over the last two decades builds on the “domino theory of regionalism”.28 At its
most general, this theory postulates that preferential trade policies hurt outsiders by way of
trade diversion.29 Outsiders then feel compelled to react, either by joining a preferential trade
agreement or by setting up an alternative one. Over time, this leads to the spread of
preferential trade agreements.
This idea has been developed in most detail by Richard Baldwin.30 Baldwin starts
from a political economy model according to which governments maximize a function of
interest-group donations, general welfare, and support from groups that oppose membership
for non-economic reasons. To explain why governments react to losses rather than
maximize gains, Baldwin assumes that losers from policies lobby more than do winners
because winners cannot profit from their gains in a competitive setting. He legitimizes this
assumption by arguing that if returns to investments increase in a sector, more firms will be
attracted to that sector, increase competition, and cause gains to be lost again. Consequently,
there is no incentive to lobby for gains; exporters will become active only when facing losses,
such as those stemming from foreign preferential trade policies. This logic, however, is
26 Manger 2005. 27 Dür 2007b. 28 Baldwin 1993. 29 For the concept of trade diversion, see Viner 1950. 30 Baldwin 1993; 1997; 2006.
9
challenged by the fact that many industries are characterized by high barriers to entry.
Among them are not only declining sectors, but also ones that are able to export exactly
because they gain oligopolistic rents in the home market. Such industries, therefore, will
favor voice over exit with or without foreign discrimination. Following this explanation,
whether or not an industry lobbies should be determined by the industry’s barriers to entry
of new capital, but not by its trade orientation (that is, whether it is an exporting or an
import-competing sector).
We formulate a slightly different explanation that resolves this problem. The
resulting “protection-for-exporters” argument assumes the existence of two trade policy
constituencies, exporters and import-competitors. Exporters benefit from better foreign
market access and import-competitors from continued protection of their sector against
foreign competition. While import-competitors tend to be highly mobilized in defense of
their interests, we expect exporters in most circumstances to be hardly politically active. The
reason is that they face substantial uncertainty with respect to the potential benefits from
engaging in lobbying for better foreign market access. Not only do they face the uncertainty
of whether they will be able to convince their own government to pursue their preferences
(an uncertainty that is shared by import-competitors), but they also face uncertainty about
the willingness of a foreign government to reduce its trade barriers. The uncertainty is even
further enhanced by the fact that trade negotiations tend to go on over quite a substantial
time, making it difficult to know the competitive situation of an exporter at the time the
agreement enters into effect. As a result, it is difficult for an exporter to predict whether she
or rather another exporter from the same country (or an exporter from another country that
may also benefit from trade liberalization) will reap the benefits of better foreign market
access.
10
In short, uncertainty strongly inhibits exporters’ lobbying for gains. In this situation,
even if some exporters manage to overcome the uncertainty and become politically active,
the balance of domestic interests will be biased in favor of import-competing interests. It
seems reasonable to expect that a government will take into account this balance of interests
when formulating its trade policy, even if domestic interests do not perfectly translate into
government policies.31 The balance of domestic interests is an important consideration for
decision-makers that want to stay in power because organized interests that are dissatisfied
with government policy will try to mobilize the public. The expectation hence is for
governments to pursue policies that satisfy import-competing interests, even if they do not
close their markets completely as there always are some offsetting pressures from the broad
public that cares about economic efficiency and producers who depend on imports. For the
puzzle at hand, the prediction is for few regional trading arrangements to come into
existence under these circumstances.
Exporters’ incentives to mobilize are substantially different when facing losses,
caused, for example, by the creation of a preferential trading arrangement among foreign
countries. In this situation, rather than having to invest in monitoring foreign markets to
gather information about export opportunities, they can simply react in a fire-brigade
manner to any losses they experience form the trade policy choices of foreign countries.
Moreover, they can be quite certain about the consequences of their lobbying activity. If they
manage to achieve the re-establishment of the market conditions that existed before the
creation of the preferential trade agreement, they should be able to regain their share of that
market. Exporters’ uncertainty of lobbying against losses, consequently, is lower than the
uncertainty of lobbying for gains. The expectation derived from this argument is that a
31 This assumption is common to a large number of studies in the field of International Political Economy. See, for example, Milner 1988; Gilligan 1997; Chase 2005.
11
stronger lobby effort by exporters should be visible in response to losses.32 To the extent
that governments are receptive to changes in the relative balance of different interests in a
country, this shift in the domestic balance of interests should give more prominence to
exporter concerns in the country’s trade policy. In particular, we expect that the country
should enter into negotiations for a trade agreement with the country in which exporters face
a loss of market access.
The strength of the effect just set out depends on the amount of trade diversion that
an agreement causes for an excluded country. The amount of trade diversion, in turn,
depends on the extent to which the exporters of the excluded country directly compete with
a member country of a preferential trade agreement in the market of the other member
country. Simplifying, it can be expected that an agreement between two developed countries
will have a high pull effect for other developed countries, but a low pull effect for
developing countries. An agreement between two developing countries, by contrast, will
have the largest effect on other developing countries. A North-South agreement, finally,
should stimulate other agreements between developed and developing countries. The logic
also suggests that the impact of a preferential agreement should be particularly severe for
countries that see a significant amount of their exports go to one of the member countries.
The reason is that the larger the share of exports concerned, the larger the potential costs,
and the larger also the political power of the exporters concerned. Summarizing, this means
that the likelihood of an agreement between countries A and B increases as the number of
preferential trade agreements A and B form part of increases; the share of exports from A
going to B and B going to A increases; and the degree of competitiveness between the
32 The same expectation of mobilization against losses can be derived from prospect theory (Kahneman and Tversky 1979; Fannis 2004). According to prospect theory, actors are more willing to engage in risky behaviour if they expect losses. While in this paper we cannot empirically test the two approaches against each other, we find the approach based on uncertainty theoretically more appealing.
12
exports of A (B) and the partner countries (C, D,…) of the other side increases. In the form
of a hypothesis:
Hypothesis: The probability of a preferential trade agreement between two
countries increases as the number of preferential agreements in which each of
them participates and the discriminatory trade effects of these agreements
increases.
It is important to stress that our argument leads to the expectation that both
conditions included in this hypothesis are necessary for the diffusion effect to come about.
Preferential trade agreements should not have an effect on the trade policy choices of third
countries unless they generate trade diversion. If we were to see that preferential agreements
spread to countries that do not suffer from trade diversion, this would be an indication that
alternative diffusion mechanism are at play, a question that we take up below.
Any explanation relying on a domino effect begs the question of what the initial
stimulus for the domino effect is, that is, what makes the first domino stone fall. The
endogenous explanation is that in some cases, governments may be able to design an
agreement that imposes costs on third countries rather than domestic import-competing
interests. In such a case, in the absence of lobbying by import-competitors, governments
may have an incentive to conclude an agreement.33 An initial agreement should be
particularly probable between adjacent countries, as in such a case exporters’ uncertainty
about the potential benefits of such a move is likely to be smallest. For some agreements, an
33 Grossman and Helpman 1995, 680.
13
explanation may also require consideration of exogenous factors, such as the geopolitical
interests of countries.
Countries could also be expected to conclude preferential trade agreements because
they expect to benefit from the external effect that we describe here. In fact, there are some
historical examples of countries using preferential trade agreements to put pressure on third
countries. Some evidence, for example, suggests that the Asian and Pacific countries may
have used the threat of preferential liberalization as part of the Asia Pacific Economic
Cooperation (APEC) to force the EU into accepting the conclusion of the Uruguay Round.34
The empirical record, however, suggests that in many cases, decision-makers did not
anticipate the external consequences of a preferential trade agreement. In some cases, they
even were surprised by these effects. Few people, for example, had predicted that the
deepening of European integration in the 1980s would have a major pull effect on third
countries, which led to the creation of the European Economic Area and the negotiation of
a series of Mediterranean agreements.
An aspect of the argument that we have ignored so far is why a member country of a
preferential agreement (country A) should accept the conclusion of a trade agreement with
an excluded country (country B). As country A recently concluded a preferential agreement
with country C, it could be hypothesized that its domestic interests will not lobby in favor of
another agreement. Import-competitors will be particularly sensitive about a further
agreement at a time when they suffer from the consequences of the initial agreement, while
exporting interests will be eager to exploit the new market opportunities. Our argument is
that country A will accept an agreement only if its exporters face losses in country B (the
34 Richardson 1993.
14
inverted logic) or because country B is so eager to reach an agreement with A that it is
willing to make major concessions.
Although we have formulated our argument using the example of bilateral
agreements, the logic also applies to plurilateral preferential agreements. For exporters in third
countries, a multilateral agreement has the same effect as a set of bilateral agreements: it
threatens access to several markets at the same country. A multilateral agreement between
countries A, C, D, and E therefore is likely to have a major pull effect on country B, if it has
major export interests in at least one of these markets and its exports are in competition in
that market with those from at least one of the other member countries. The precise reaction
of country B to this plurilateral agreement will depend on its export interests. If its exports
are concentrated in A, it will conclude a bilateral agreement with that country. If it has export
interests in more than one of these markets, however, it may decide to join the existing
agreement. This is the explanation that we provide for the repeated rounds of enlargement
of the European Union.
What we do no consider in this paper is that a country may react to discrimination in
ways other than signing a trade agreement with one of more of the member countries of a
preferential agreement. For one, it may threaten with retaliation against countries that
impose costs on its exporters. When the European Union moved towards a deepening of
integration in the late 1980s, the U.S. responded with threats to all proposals that had the
potential of imposing costs on its exporters. Such threats can only be used by structurally
powerful countries, however. Weaker countries responded to the Single Market Program
with requests for bilateral agreements, as set out in this paper. A second possible response to
discrimination is a call for multilateral trade liberalization. Again the U.S. reaction to
European integration best illustrates this tactic. The creation of the European Economic
15
Community in the late 1950s caused concern among American exporters. Instead of signing
a preferential agreement with the new trading entity, the U.S. used the Kennedy Round of
world trade negotiations (1964-67) to reduce the discrimination resulting from the European
move.35 Finally, a government may decide to compensate exporters that face costs from
trade diversion by way of a subsidy. World trade rules, however, impose strict limits on the
use of subsidies; governments violating these rules have to fear the imposition of
countervailing duties. Disregarding these alternative tactics leads us to underestimate the
external effect of preferential trade agreements.
DATA AND OPERATIONALIZATION
Only very few studies have tried to quantitatively test the basic idea underlying the argument
about interdependence in the creation of preferential trade agreements.36 What is more, these
existing studies are characterized by a series of shortcomings. Early quantitative studies, for
example, did not explicitly model the spatial correlation at the heart of the theoretical
argument. More recent studies using spatial weights matrixes either restrict the analysis to a
small sample of countries or take a cross-section approach.37 By using time-series rather than
cross-sectional data, establishing an authoritative list of trade agreements, designing a
quantitative test that captures the trade diversion logic that underlies our argument as closely
as possible, and controlling for alternative diffusion mechanism, we improve on the existing
literature with respect to both data and operationalization.
We test our argument on a database of preferential trade agreements among 168
countries between 1990 and 2007. As is evident from Figure 1 above, relatively few
35 Dür 2008. 36 Among the exceptions are Mansfield 1998; Rieder 2006; Egger and Larch 2008. 37 Rieder (2006) restricts the analysis to 25 developed countries and Egger and Larch (2008) adopt a cross-section approach.
16
agreements were signed before 1990, legitimating our choice to start the analysis in that year.
Starting in 1990 also makes sense from a methodological point of view. By extending the
dataset to the years before 1990, we would have to tackle the fact that the Cold War
environment was quite distinct for most countries than the post-Cold War environment. As
Kevin Clarke has forcefully shown, including control variables to deal with omitted variable
bias associated with such a shift may increase rather than reduce this bias.38 We thus follow
his recommendation of substituting research design for control variables by limiting the
dataset to the post-Cold War period. With respect to country coverage, while we have tried
to include as many countries as possible in our analysis, we had to exclude some (mostly very
small) countries owing to data restrictions. This leads to the elimination of a few dyads with
preferential trade agreements, especially in the Caribbean region. We also exclude
Montenegro as it only came into existence in 2006 and hence would have been in the
database for only two years. A few other countries that became independent after 1990 enter
the database in the year of their independence.
The dyads included in the analysis are non-directional, that is, we do not distinguish
between the country pair Albania-Argentina and the reverse country pair Argentina-Albania.
The reason for using non-directed dyads is that we do not know which country started the
negotiations for a preferential trade agreement. While in single case studies it may be possible
to find out exactly which country made the first step in calling for a trade agreement, doing
so for the large number of agreements included in our analysis is not practical. What is more,
using non-directed dyads makes sense from a theoretical point of view: we expect an
agreement to come about only if both countries feel some pressure to engage in
negotiations. In most cases, therefore, we would expect the future member countries to
38 Clarke 2005.
17
informally agree on the need for an agreement before they formally launch the negotiations.
In total, we consider up to 14,028 dyads per year for a total number of 225,833 observations.
The dependent variable in our analysis is whether two countries sign a preferential
trade agreement in a specific year. We opted for the year of signature rather than the year of
entry into force of an agreement, as signing an agreement is an important indication that
governments respond to exporter lobbying. The year of signature is also important for the
effect that agreements have, since it is in this moment that exporters in third countries
should become worried about the potential negative consequences for them. We invested
substantial effort in establishing an authoritative list of trade agreements signed between
1990 and 2007. Using three different databases, namely the list of regional trade agreements
notified with the World Trade Organization, the Tuck Trade Agreements Database, and the
McGill Faculty of Law Preferential Trade Agreements Database, but excluding partial-scope
agreements and agreements that include no preferential treatment, we find that 1600 dyads
formed a preferential trade agreement between 1990 and 2007.39
For our analysis, we also needed to know which dyads already formed part of a
preferential trade agreement in 1990, since dyads with an agreement drop out from our
analysis. Our database hence includes all agreements effectively implemented between 1945
and 1989 that were still in existence in 1990, and all new agreements signed between 1990
and 2007. We exclude a few agreements from our database that formally were in existence in
1990 but had not been effectively implemented. Examples are the Latin American
Integration Association, which did not lead to any significant preferential tariff reductions,
and the Economic Community of Central African States (until 1993, when member
countries signed a revised agreement). Such agreements, which only exist on paper, do not
39 These databases are available at http://www.wto.org/english/tratop_e/region_e/summary_e.xls; http://www.dartmouth.edu/~tradedb/; and http://ptas.mcgill.ca/ [all last accessed August 18, 2008].
18
have an external effect, and thus should not contribute to the domino effect we are
interested in. The agreements that we consider to be effectively implemented with
discriminatory consequences as of 1 January 1990 are: the EU; the European Free Trade
Association (EFTA); the agreements between the EU and EFTA countries; the agreements
between the EU and Cyprus, Israel, and Malta; the agreements between the U.S. and Canada
and Israel; the Caribbean Community; and the South African Customs Union.
We do not consider second or third agreements signed between two countries. This
is an important restriction especially for European dyads, where we see a stepwise deepening
of integration. We also see a transformation of bilateral agreements between the European
Union and third countries across Europe into accession treaties. All Central and Eastern
European countries, for example, signed bilateral free trade agreements with the EU in the
early 1990s. Since dyads are ignored once they concluded an agreement, events such as the
accession to the EU of ten of these countries in 2004 do not figure in our analysis. While the
deepening of integration can have effects similar to those captured by our theoretical
argument (and can be a reaction to preferential trade agreements among third countries), we
decided to exclude these cases from our analysis to secure unit homogeneity (as the political
economy of deepening an agreement may be slightly different from the political economy of
an initial agreement). More generally, by opting for a dichotomous dependent variable, we
abstract from the fact that some preferential agreements are more far-reaching, and hence
potentially more trade-diverting, than others.
Policy Diffusion: Competition and Emulation
The model that we estimate includes a spatial weights matrix and control variables for both
the dyad under consideration and potential external shocks. We thus estimate the following
equation:
19
yit = βxit + δwiyt-1+ εi (1)
where β and δ are the coefficients and wi is the ith row of the spatial weights matrix. We use
three different approaches to estimate this model. First, in line with earlier research, we
estimate a Cox proportional hazards model, adjusted for clustering on dyads.40 The
advantage of using the Cox model is that it does not require any assumption about the shape
of the underlying survival distribution. As is common practice in recent research on the
statistical analysis of panel data with a binary dependent variable, we base significance test on
Huber (robust) standard errors.41 These standard errors can take account of possible
heteroskedasticity (serial correlation) or intra-group correlation of the data. Second, we use a
frailty model (Gamma distributed) to control for the heterogeneity between groups, which turns
out to be statistically significant in our case. As Janet Box-Steffensmeier and Bradford Jones
argue, heterogeneity can result from the omission of relevant variables.42 Not dealing with
heterogeneity can lead to an underestimation of the effect of covariates that increase the
hazard rate and an overestimation of the effect of covariates that reduce the hazard rate.
Finally, since our dataset is heavily zero-inflated, we also estimate the models using a rare
events logistic regression.43 The use of this approach is recommended since common logistic
regression underestimates the impact of the explanatory variables on the probability of the
rare event. In addition, there is the risk that the standard errors are biased with a large
number of zeros in the dependent variable.
The main independent variable is an N*N*t spatial weights (also called connectivity)
matrix. A spatial weight matrix measures the impact of a policy change in a dyad on all other
40 The study by Elkins et al. on the diffusion of bilateral investment agreements is also based on the Cox model. Darmofal (forthcoming) provides an extensive analysis of the use of survival models with spatial effects. 41 Beck 2008, 486. 42 Box-Steffensmeier and Jones 2004, 141. 43 In our dataset, only about 0.7 percent of the dyads have a score of 1.
20
dyads. It weighs the policy change by specific factors, such as spatial proximity or degree of
economic interdependence. In our case, the policy change is whether a dyad signed an
agreement in the last five years. We opt for a five year period as we think that while it may
take some time for exporters in third countries to react to the creation of a preferential trade
agreement, and for this reaction to have an impact on the trade policies of a country, after
some time the external effect of a preferential trade agreement should disappear. After five
years, exporters will either have been successful in convincing their government to reach an
agreement with the members of a preferential trade agreement or will have adapted to the
new situation.
We weigh the influence of the policy change in other dyads in a way that
approximates the trade diversion logic as directly as possible. The hypothesis set out above
leads us to the expectation that the pressure on country B to respond to a preferential trade
agreement between countries A and C by signing an agreement with A should depend on the
importance of market A for B and the degree of competition between the exports to A by B
and C. In form of a formula, the spatial weight for dyad AB is as follows:44
∑∑
+
=
,...,d,...a_c,
d...b_c,
ba
,...,d,...b_c,
d...a_c,
ab n*c
en*
c
e
lkdcabk (2)
where kab is greater than 0 if countries A and B are connected. In this formula, e is the share
of a country’s exports going to the other country, c is the degree of competition between two
countries and n a variable that takes on the value 1 if country A (B) signed an agreement with
countries C, D, and so on between one and five years ago. The variable is lagged by one year
44 The spatial matrices have been calculated using the software MATLAB 7.0 employing a program designed by the authors for this purpose. Although frequently done in the literature (see Freanzese and Hays 2008, 580), we do not row-standardize our connectivity matrix since we do not have any theoretical reason to do so and since row-standardization may influence the results and may impact inference (see Plümper and Neumayer 2008, 26).
21
to avoid simultaneity bias. This may lead to an underestimation of the spatial effect, if
countries already react to other countries’ negotiations of preferential trade agreements. An
example of this would be African countries that initially are reluctant to sign an Economic
Partnership Agreement with the EU, and then still jump on the bandwagon as they fear
exclusion from agreements signed by the EU and other African countries. The subscripts a,
b, and so on denote the countries.
The formula has two parts: the first part assesses the pressure on A resulting from
B’s trade agreements and the second part the pressure on B resulting from A’s trade
agreements. The additive term captures the idea that the probability that A and B sign an
agreement depends on both sides’ incentive to conclude one. As set out above, an agreement
will only come about if either both countries face exclusion in the other’s market or one
country faces very large costs and thus will be willing to make major concessions to achieve
an agreement.
With respect to the importance of the other country’s market, we use dyadic exports
as a share of a country’s total exports. A potential problem with this is that export shares are
partly endogenous to our argument. The share of exports of country A going to country B
should decrease as country B signs a preferential trade agreement with country C, at least as
long as countries A and C export the same goods. We deal with this endogeneity problem by
lagging the matrix by one year. The term used to denote this matrix below is “trade and
competition”.
One way of measuring the degree to which two countries compete on the same
market is to disaggregate trade flows to the sector or even product level and then correlating
the direction of trade flows. However, weak trade data for many of the countries that we
22
include in our analysis made us opt for a proxy measure instead.45 We use the (natural log of
the) difference between the per capita Gross Domestic Product (GDP) of countries B and C
as a proxy for the extent that these two countries compete in the market of country A.46 The
assumption underlying this operationalization is that countries with a similar GDP per capita
have a similar factor endowment and thus should export the same goods. A North-North
agreement should have an impact on other Northern countries47; a South-South agreement
on other Southern countries; and a North-South agreement should make Northern countries
conclude an agreement with the Southern and Southern countries with the Northern
member of the agreement. For example, the EU should have reacted to the North American
Free Trade Agreement by signing an agreement with Mexico, as it exports similar goods to
that country as does the US.48 That it did not sign an agreement with the US also supports
our logic, as the EU’s exports to the US do not compete with those from Mexico.
Figures 2a and 2b illustrate how this variable changes for two cases. In Figure 2a, we
show the spatial weight for the dyad Bolivia and Chile. On November 29, 1990, the Andean
Pact (now Andean Community), of which Bolivia is a member but Chile is not, decided to
establish a free trade area by January 1993. This decision increased the pressure on Chile to
conclude a trade agreement with Bolivia. The pressure on Chile grew even stronger as a
result of the September 10, 1994, free trade agreement between Bolivia and Mexico. It is no
wonder then that Bolivia and Chile signed an agreement one year later. In Figure 2b, the
agreement between the Czech Republic and the EU has only little impact on the dyad Czech
45 In fact, even at the aggregate level, dyadic trade data is quite problematic, as it includes many missing values and exhibits major jumps in the time series for less developed countries. See also Gleditsch 2002. 46 We use natural logarithms of many of the variables, since they are characterized by frequent (economic and geographical variables) or occasional (spatial variables) large observations. 47 Intra-industry trade, which is important between developed countries at a similar stage of development, lowers the potential for trade diversion. The operationalization used here thus makes us overestimate the pressure that preferential agreements among developed countries exert on other developed countries. The results are consequently biased against our argument. 48 In fact, this is what happened. See Dür 2007a.
23
Republic – Bulgaria, as Bulgaria is expected to export different goods to the Czech Republic
than the then member states of the EU. The pressure on Bulgaria increased as a result of the
agreements between the Czech Republic and Latvia (1993) and the accession of Romania to
the Central European Free Trade Agreement (CEFTA) in 1997. The logical result was the
conclusion of a trade agreement between the Czech Republic and Bulgaria in 1998, as part of
the latter country’s accession to CEFTA.
FIGURES 2a and b APPROXIMATELY HERE
As indicated above, several alternative causal mechanisms could drive the diffusion
of trade agreements. In the empirical analysis below, we control for the possibility that
diffusion is a result of emulation or security externalities. Emulation is defined as
ritualistically “following or doing oppositely of others”.49 It is most likely among countries
that are culturally close. The expectation thus is that the probability of a preferential trade
agreement between countries A and B increases, as the number of preferential agreements
that A and B participate in increases and the cultural distance between A and B decreases.
Building on work by Zachary Elkins, Andrew Guzman and Beth Simmons, we construct
three different spatial weights matrices measuring cultural proximity to capture this effect.50
Each of the matrices uses a different proxy for cultural distance: whether two countries share
the same predominant language, predominant religion, and a common colonial past. We also
control for the possibility of diffusion resulting from security externality. To capture this
effect, we calculate a spatial weight matrix that increases the probability of countries A and B
49 Franzese and Hays 2008, 572. 50 Elkins et al. 2006, 831.
24
signing an agreement if country C, with which B has had a military conflict since World War
II, signed a preferential trade agreement with another country in the last five years.
Control Variables
In our models, we also take into account a series of variables that characterize the dyad
under analysis and the context in which a dyad considers concluding an agreement. Doing so
is vital to avoid overestimating the effect of the spatial lag, as parallel policy choices may be a
result of correlated unit-level factors or exogenous shocks that are common to various
dyads.51 Thus, in accordance with previous studies in the field, we include several economic,
geographical, and political variables as control variables in our base model. Most of these
variables are lagged by one year to avoid endogeneity problems. In the robustness checks
below, we add further control variables.
Concerning the economic variables, we control for the amount of trade between the
two countries, as previous research has shown that as trade between countries increases, the
probability of forming a preferential trade agreement increases as well (TRADE). It can also
be hypothesized that signing an agreement between two economies of relatively equal size
should be easier that signing one between a large and a small economy. Among the reasons
to expect such an effect is that the small country may fear becoming overly dependent on
the large country and that for the large country the economic benefits of an agreement with
a small country are likely to be small. The welfare gains from an agreement may also increase
as the parties to an agreement become more similar in economic size.52 The measure that we
use for this variable is the absolute difference in GDP between the two countries (SIM).
We also include a measure of the size of the economy of the two countries to
capture the idea that the larger the countries participating in a preferential trade agreement,
51 Franzese and Hays, 2008. 52 Baier and Bergstrand 2004.
25
the larger the economic gains. As Scott Baier and Jeffrey Bergstrand argue, a preferential
agreement between two large economies increases the volume of trade in more varieties than
one between two small economies.53 In addition, the larger increase in trade among two large
countries causes a larger net expansion of demand and hence a larger rise in real income. We
capture this idea by including the GDP of the smaller of the two countries in a dyad (GDP).
A further factor that potentially influences the likelihood of an agreement between a pair of
countries is the level of development. The more developed the two countries, the easier they
should find it to conclude an agreement. This is so for two reasons. First, a country with a
highly developed economy is less dependent on tariff revenues. Second, a developed country
is in a better position to compensate societal groups that face adjustment costs due to trade
liberalization.54 The variable that captures this argument is the absolute difference in GDP
per capita (GDP PER CAPITA). As with other variables that are measured at the level of the
state, we convert this one into a dyadic variable by opting for the lower of the two values as
the one characterizing the dyad.
Two control variables capture domestic and international political factors. At the
international level, it is quite straightforward to assume that military allies should be more
likely to sign an agreement than other pairs of countries (ALLIANCE). At the domestic level,
previous research has shown that democratic pairs of countries tend to sign more
preferential trade agreements than non-democratic or mixed pairs.55 We use the seven point
Freedom House scale of democracy to measure this variable, with 1 being the value for a
completely free and 7 the value for a completely oppressive regime (DEMOCRACY).56 The
53 Ibid., 45. 54 Ruggie 1982. 55 Mansfield et al. 2002. 56 Freedom House 2007.
26
advantage of the Freedom House index over others is that it covers all of the countries in
our dataset and provides values for up to 2007.
Finally, we include two variables that measure the geographic distance between
countries, as previous research has shown an effect of distance on the likelihood of signing a
preferential agreement.57 On the one hand, neighboring countries can be expected to have a
higher probability of signing an agreement. Not only are there on average closer economic
links between neighboring countries, but also the political links tend to be stronger. We thus
expect countries that share a common border to be more likely to sign an agreement
(CONTIGUITY). On the other hand, since trade costs increase with distance, geographically
closer countries are more likely to form a preferential trade agreement. We thus include the
(natural logarithm) distance in kilometers between the two capitals of the pair of countries in
our base model (DISTANCE).
FINDINGS
In a first step, we estimate four different models (see Table 1). First, we report the findings
of a Cox proportional hazards model, adjusted for clusters on dyads, with the restricted set
of control variables. The findings are strongly supportive of our argument. The coefficient
for the domino effect has the right sign and is statistically significant at the 0.01 level. Some
of the variables capturing the alternative diffusion mechanisms are also statistically
significant. Countries seem to be influenced in their decision to conclude agreements by the
agreements concluded by other countries with the same language and colonial heritage.
Religion is the only of these three variables capturing the emulation argument that is not
statistically significant. Neither is the rivalry argument supported by the empirical
57 Krugman 1992; Baier and Bergstrand 2004.
27
examination. Countries do not seem to be reacting to the agreements concluded by countries
that may pose a military threat.
TABLE 1 APPROXIMATELY HERE
Many of the control variables that have been shown to be important in previous
research also turn out to be significant in this model, giving added plausibility to our
findings. For one, a pair of countries with a strong trade link is more likely to form a trade
agreement. Furthermore, pairs of countries with relatively large economies are more likely to
sign an agreement. Security concerns seem to play a role as well, as countries that form part
of the same alliance are more likely to form an agreement. Moreover, democratic pairs of
countries are less prone to conclude an agreement, thus confirming previous research.58 Also
intuitive is the finding that distance reduces the likelihood of an agreement. Interestingly,
however, contiguous countries are less likely to form an agreement than countries that do not
share a common border.
Model 1 thus provides strong support for the argument that the signing of a
preferential agreement among two countries has an effect on the probability of other
countries signing a preferential trade agreement with them. We include figures to illustrate
the magnitude of this effect (see Figures 3a, 3b, 4a, and 4b). Figure 3a shows the effect of a
change in the importance of a market on the diffusion effect. As set out in the hypothesis
above, the spatial effect of a trade agreement between two countries on a third country is
much stronger if the excluded country has substantial export interests in at least one of these
two countries. Figure 3b shows the same effect for the second variable that forms part of the
58 Mansfield et al. 2002.
28
trade and competition matrix. The more similar the exports of country B to those of country
C, the greater the threat of trade diversion in country A, and thus the greater the incentive
for country B to sign an agreement with country A. Figures 4a and 4b compare the
substantive effects of the trade and competition matrix and the common colonial heritage
matrix. As the graphs show, the effect is stronger for the competition variable.
FIGURES 3a, b and 4a, b APPROXIMATELY HERE
Models 2, 3, and 4 provide further support for our argument. In Model 2, we include
additional control variables to check the robustness of our base model. The first of these is
economic growth, as an economic downturn may increase the probability of a PTA being
formed.59 We use the average value for the two countries (GDP GROWTH). We also control
for the export orientation of countries, that is, the importance that exports have as a
percentage of the overall economy.60 The more export oriented a country is, the larger the
political influence of export interests should be. With exporters expected to benefit from a
preferential trade agreement, an increase in exporters’ power should increase the probability
that this country signs a preferential agreement. Since members of the World Trade
Organization (WTO) tend to have more similar trade policies than countries that do not
form part of this international organization, dyads in which both countries are WTO
members should be more likely to conclude an agreement (WTO).
Furthermore, we consider the possibility that during multilateral trade negotiations in
the WTO countries’ propensity to conclude preferential trade agreements increases (WTO
59 See for example Mattli 1999. 60 As is common in the literature, we measure export orientation by the natural logarithm exports to GDP ratio in year t-1. See also Rodrik 1995.
29
ROUND). We also control for the argument reported above that involvement in trade disputes
may influence a pair’s propensity to conclude a trade agreement. Having a trade dispute with
the other side should decrease the likelihood of an agreement (TRADE DISPUTE), while
having a dispute with a third party should increase it (TRADE DISPUTE THIRD PARTY). As
culturally similar countries may find it easier to negotiate an international agreement, we also
include three proxies for cultural similarity, namely common language, same religion, and
common colonial heritage (LANGUAGE, RELIGION, and COLONY). Finally, since being an
island may influence a country’s willingness to sign an agreement – namely increasing the
willingness to overpass its geographical disadvantages – we also control for this variable in
our extended models (ISLAND).
The results of the model including these control variables are very similar to those
reported in Model 1. Among the new variables, most have the expected effect. For example,
a strong export orientation makes countries eager to form preferential agreements. This
finding provides support for our causal mechanism, which draws attention to the role of
exporters in lobbying for preferential trade agreements. Two member countries of the WTO
are more likely to conclude an agreement than if at least one country of a dyad is not a
member of the WTO. A trade dispute between the two countries, however, makes them less
likely to conclude an agreement. Interestingly, the previous finding by Walter Mattli that a
lack of economic growth makes countries sign an agreement is not supported.61
In Models 3 and 4 we change the econometric approach, but without that changing
the substantive findings. Noteworthy is the fact that in the model in which we use a rare
events logistic regression (Model 4), the substantive effect of our key variable is even larger
61 Mattli 1999.
30
than in the other models. Overall, across all four models the support for our argument is
thus very strong.
ROBUSTNESS CHECKS
To check the robustness of our results, we made a series of changes to our base model. For
all of the changes discussed below, the results are roughly comparable to the ones presented
and are available upon request. First, we estimated models in which we assume that
preferential trade agreements have an impact on third countries for three and seven years
after their signature. These changes control for the robustness of our initial hunch of a five-
year effect. Second, with respect to the importance of the export market, we use the inverse
of the geographical distance between A and B as a proxy for the amount of trade between
the two countries. The advantage of using distance is that the quality of this data is very good
(while data on dyadic trade flows is problematic). Moreover, distance has been shown to be a
very important determinant of trade flows. This is a result of the fact that trade costs
increase with geographic distance. By using distance we also avoid potential endogeneity
problems arising with trade flows as discussed below.
Third, we disaggregate the spatial weights matrix set out above into its component
parts. On the one hand, we estimate a model in which the spatial weight is purely determined
by the difference in per capita GDP between the excluded country and the potential
competitor. On the other hand, we assess a model with a spatial weights matrix calculated by
solely considering the excluded country’s exports to the discriminating country. The
expectation for these two models is for the spatial effects to be statistically significant but of
smaller magnitude than the ones reported above. This expectation is borne out by the
analysis.
31
Finally, we estimated a series of models in which we dropped all dyads with (1) an
EU country, (2) an EU or EFTA country, and (3) two Northern countries. The reason for
excluding EU and EFTA countries is that both trading entities may be considered unitary
actors in the international trading system. Our expectation was that relying on member states
(as done above) rather than the aggregate trading entities should make us underestimate the
competition effect in which we are interested. The following example illustrates this
expectation: the agreement between the EU and Mexico (2000) is best seen as a response to
the North American Free Trade Agreement.62 The countries within the EU that pushed for
this agreement were Spain, France and Germany. By coding this agreement for 15 EU
member countries, including countries such as Ireland and Finland that had no interest in
the agreement with Mexico, the competition effect is diluted. The EU creates further
difficulties for our analysis: joining the EU means that the new member country has to sign
up to all trade agreements that the EU forms part of at the time of accession. While a
country such as Hungary may have joined the EU because of the logic set out in our
argument, it was probably hardly interested in signing an agreement with Mexico.
Nevertheless, in our analysis, there is no difference between accession and accepting
agreements with third countries.
TABLE 2 APPROXIMATELY HERE
Table 2 shows the results of the models excluding EU and EFTA countries. In fact,
as expected, the competition effect is stronger than in the base model. The fact that the
values for all other variables are very similar to those reported above provides a strong
62 Dür 2007a.
32
indication that our results are very robust. The one variable that becomes statistically
significant in Models 5 and 6 is rivalry. This is very intuitive, as military conflict has not
played a role in Europe since World War II, but it does play a role in other continents. The
most interesting finding, however, is that democracy no longer plays a role once the
European countries are excluded from the dataset. This suggests that earlier findings of pairs
of democracies being more likely to sign an agreement were driven by the European
countries alone.63 In Model 7, we dropped all the dyads between two developed economies
to show the impact of policy diffusion on North-South and South-South preferential
agreements that are a special feature of the current wave of regionalism. Again the results
concur with the previous models.
CONCLUSION
This analysis has shown that the formation of preferential trade agreements is indeed an
interdependent process. A country forms an agreement with another country if it competes
on that market with third countries that already have preferential access. In making this
point, we have contributed a quantitative test of an argument that is quite prominent in the
literature on regionalism. Existing research offers several qualitative case studies of how
excluded countries react to the creation of a preferential trade agreement. Nevertheless,
quantitative research on this issue has so far been limited to a very small number of studies,
which moreover are hampered by several shortcomings. We have been careful in designing a
direct test of the argument and gathering more reliable data on the existence of preferential
trade agreements than had been done before.
Our paper also contributes to the literature on spatial effects (policy diffusion), by
calculating a trade-weighted matrix rather than one based solely on geographical distance,
63 Mansfield et al. 2002.
33
and by taking into account extra-dyadic relations. The time-varying nature of trade flows
created major problems for earlier studies, which we overcome in this problem. To our
knowledge, so far there has not been any attempt made at including extra-dyadic
relationships in the definition of spatial lags, although doing so may be consistent with
theory in many instances. For example, in the diffusion of bilateral investment treaties, the
effect of one agreement on other countries’ willingness to conclude an agreement may also
depend on the relationship between the third country and the developing country that signed
the initial agreement.
In future research, the present analysis could be extended in several respects. For
one, it would be interesting to take into account excluded countries’ possibility of forming a
rival agreement, rather than signing an agreement with a member country of a preferential
trade agreement. The classic case for such a rival agreement is the formation of the
European Free Trade Agreement in response to the creation of the European Economic
Community. Moreover, it would make sense to consider the fact that some dyads may
deepen their agreements in response to other dyads concluding agreements, and that the
deepening of agreements may lead other countries to seek an agreement as well. For
example, the Single European Act (1987) arguably increased the interest among
Mediterranean countries in signing a trade agreement with the EU. Finally, a good argument
can be made that current preferential trade agreements not only threaten trade but also
foreign direct investments. The North American Free Trade Agreement, for example, not
only created problems for European companies exporting to Mexico, but also to European
companies interested in investing in Mexico. A future study may take into account the
contents of agreements and foreign investment flows in providing an even more
comprehensive examination of the diffusion story.
34
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39
Table 1: Testing the Domino Argument Covariates Model 1 Model 2 Model 3 Model 464
Estimation Cox Model (clusters on
dyads)
Cox Model (clusters on
dyads)
Cox Model (Gamma Frailty)
ReLogit (clusters on
dyads) Domino theory
TRADE & COMPETITION 0.24 ** (0.09)
0.24 ** (0.09)
0.23 ** (0.10)
0.36 ** (0.12)
Alternative diffusion SPATIAL LANGUAGE 0.12 **
(0.03) 0.10 ** (0.03)
0.25 ** (0.03)
0.18 ** (0.03)
SPATIAL COLONY 0.16 ** (0.04)
0.14 ** (0.03)
0.11 ** (0.03)
0.12 ** (0.04)
SPATIAL RELIGION -0.01 (0.03)
-0.05 (0.03)
-0.03 (0.03)
-0.06 * (0.02)
RIVALRY 0.07 (0.07)
0.12 (0.07)
0.13 (0.08)
0.19 (0.11)
Control variables TRADE 0.08 **
(0.03) 0.07 ** (0.03)
0.08 ** (0.03)
0.12 ** (0.04)
SIM 0.003 (0.13)
0.04 (0.02)
0.03 (0.03)
-0.03 (0.03)
GDP 0.31 ** (0.03)
0.34 ** (0.03)
0.48 ** (0.03)
0.58 ** (0.04)
GDP PER CAPITA 0.003 (0.01)
0.004 (0.01)
0.004 (0.01)
0.02 (0.01)
ALLIANCE 0.58 ** (0.06)
0.56 ** (0.07)
0.61 ** (0.08)
0.54 ** (0.09)
DEMOCRACY -0.12 ** (0.02)
-0.09 ** (0.02)
-0.12 ** (0.02)
-0.13 ** (0.02)
CONTIGUITY -0.73 ** (0.17)
-0.77 ** (0.16)
-0.23 (0.18)
-0.22 (0.23)
DISTANCE -1.16 ** (0.07)
-1.15 ** (0.07)
-2.24 ** (0.05)
-2.242 ** (0.06)
GDP GROWTH -0.01 (0.004)
-0.01 ** (0.004)
-0.01 (0.01)
EXPORT ORIENTATION 0.10 ** (0.03)
0.10 ** (0.04)
0.03 (0.04)
WTO 0.25 ** (0.07)
0.38 ** (0.08)
0.24 ** (0.09)
WTO ROUND
0.68 ** (0.10)
0.78 ** (0.10)
0.82 ** (0.09)
TRADE DISPUTE -1.63 ** (0.55)
-1.60 ** (0.58)
-1.72 ** (0.61)
TRADE DISPUTE THIRD
PARTY 0.05
(0.07) 0.01
(0.08) 0.11 (0.1)
LANGUAGE
-0.03 (0.15)
0.17 (0.13)
0.27 * (0.13)
RELIGION
0.27 ** (0.08)
0.33 ** (0.09)
0.58 ** (0.10)
COLONY
0.28 * (0.16)
0.20 * (0.11)
0.25 * (0.12)
ISLAND 0.23 ** (0.07)
0.32 ** (0.07)
0.57 ** (0.09)
Observations 225,833 225,833 225,833 225,833 Number of dyads signing a PTA 1,600 1,600 1,600 1,600
Log likelihood -13,510.19 -13,460.39 -13,119.20
Notes: standard errors are in parentheses. ** Significant at 1%, * significant at 5%.
64 The cubic natural spline functions are not reported. All spline functions are statistically significant at the 1 per cent level.
40
Table 2: Robustness Checks
Covariates Model 5 (excluding the EU)
Model 6 (excluding the EU and
EFTA)
Model 7 (excluding North-North
dyads)
Estimation Cox Model (clusters on dyads)
Cox Model (clusters on dyads)
Cox Model (clusters on dyads)
Domino effect TRADE & COMPETITION 0.31 **
(0.08) 0.28 ** (0.08)
0.24 ** (0.09)
Alternative diffusion LANGUAGE 0.20 **
(0.03) 0.20 ** (0.03)
0.13 ** (0.03)
COLONY 0.17 ** (0.05)
0.21 ** (0.05)
0.17 ** (0.04)
RELIGION -0.02 (0.03)
-0.003 (0.03)
-0.004 (0.03)
RIVALRY 0.18 * (0.08)
0.22 ** (0.08)
0.09 (0.07)
Dyadic controls TRADE 0.08 **
(0.03) 0.07 * (0.03)
0.08 ** (0.02)
SIM 0.01 (0.02)
0.03 (0.02)
0.01 (0.02)
GDP 0.30 ** (0.03)
0.28 ** (0.03)
0.34 ** (0.02)
GDP PER CAPITA 0.03 ** (0.01)
0.03 (0.01)
0.03 ** (0.01)
ALLIANCE 0.74 ** (0.08)
0.80 ** (0.09)
0.61 ** (0.07)
DEMOCRACY -0.02 (0.02)
-0.04 (0.02)
-0.11 ** (0.02)
CONTIGUITY -0.40 * (0.16)
-0.29 (0.17)
-0.72 ** (0.17)
DISTANCE -0.97 ** (0.08)
-1.02 ** (0.09)
-1.15 ** (0.07)
Observations 185,234 176,492 221,561 Number of dyads signing a PTA 1,159 1,053 1,535
Log likelihood -9,509.64 -8,539.71 -13,460.39
Notes: standard errors are in parentheses. **Significant at 1%, *significant at 5%.
41
Figure 1: The proliferation of preferential trade agreements, 1990-2007
42
Figures 2a and b: The spatial weights
43
Figures 3a, b. Cox model clusters on dyads: survival estimates for Trade and competition, comparing important versus irrelevant trade partner and close versus not close competitors.
0.60
0.70
0.80
0.90
1.00
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Time Period
Export share = 0 Export share >= 20%
Kaplan-Meier survival estimates
0.60
0.70
0.80
0.90
1.00
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Time Period
Not close competitor Close competitor
Kaplan-Meier survival estimates
Figures 4a, b. Cox model clusters on dyads: survival estimates for trade & competition and common colonial past.
.6.7
.8.9
1S
urv
iva
l
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Time Period
Trade and competition = min Trade and competition = max
Survival Estimates
.6.7
.8.9
1S
urv
ival
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Time Period
Common colonial past = min Common colonial past = max
Survival Estimates
Data Appendix
Variables Mean Std. deviation Minimum Maximum Data sources
Dependent variable Average survival rate 0.01 0.08 0 1 Domino effect DISTANCE AND COMPETITION
TRADE AND COMPETITION 0.63 0.03
0.90 0.20
0 0
7.99 6.74
(1) (1)
Competing Arguments SPATIAL LANGUAGE SPATIAL RELIGION SPATIAL COLONY
RIVALRY
0.91 1.58 1.68 0.16
1.32 1.51 1.57 0.41
0 0 0 0
9.36 9.91 9.36
4
(2) (3) (2) (4)
Controls SIM GDP RLF
GDP PER CAPITA GDP GROWTH
TRADE TRADE DEPENDENCE EXPORT ORIENTATION
ALLIANCE DEMOCRACY DISTANCE CONTIGUITY
WTO TRADE DISPUTE
DISPUTE WITH THIRD PARTY WTO ROUND LANGUAGE RELIGION COLONY ISLAND
3.70 1.77 9.14 1.71 0.33 8.84
0.0003 5.99 0.13 4.73 8.69 0.02 0.51 0.005 0.28 0.65 0.08 0.15 0.15 0.28
2.07 1.25 11.46 3.46 6.63 1.32 0.04 1.50 0.34 2.01 0.75 0.14 0.50 0.07 0.45 0.48 0.27 0.37 0.36 0.45
0 0.10
0 0
-52.6 3.37
0 1.55
0 1
2.35 0 0 0 0 0 0 0 0 0
9.49 8.57 89.82 62.91 35.2 13.68 0.59 12.93
1 7
9.90 1 1 1 1 1 1 1 1 1
(1) (1) (1) (1) (1) (1) (1) (1) (4) (5) (2) (2) (6) (7) (6) (8) (3) (2) (2) (2)
Sources: (1) IMF; (2) CEPII (2005) (3) Encyclopedia Britannica Book of the Year 2001; (4) Correlates of War dataset; (5) Freedom House (2007); (6) World Trade Organization (2008); (7) Horn and Mavroidis (2006); (8) Compiled by the authors.
